Category Archives: finance

Prisoner of Speed

A favourite podcast of mine is known in our household as “Danny’s podcast” in honour of the friend who first put me on to it. The podcast is better known as Radiolab and last week’s episode turned on the theme of Speed. After answering the question, what is the fastest sense, attention turned to high-frequency trading. As the Radiolab hosts are more comfortable with science than finance, they turned for assistance to David Kestenbaum from the Planet Money podcast.

In a past Mule post, I expressed reservations about the merits of high-frequency trading. Just last year, there was talk in the European parliament of enforcing a delay on electronic trading. Some critics argue that high-frequency trading creates instability in financial markets and may have been to blame for the “flash crash” of 2010.

One of the more intriguing aspects of high-frequency trading was brought out in the podcast during an interview with a technologist from the US trading firm Tradeworx. Bemoaning the cost of constantly competing to allow faster and faster trading (millions of dollars are being thrown at shaving milliseconds from the time to send trades to an exchange), he said that high-frequency traders were caught in a prisoner’s dilemma.

The prisoner’s dilemma is a staple of the study of the branch of mathematics known as “game theory“, which seeks to analyse strategic decision-making. Here is a quick overview for anyone unfamiliar with it.

Two criminals are arrested and taken to separate cells to ensure they cannot communicate with one another. The police have enough evidence to send each man to jail for one year. With a confession the police could get a conviction on a more serious charge. So, the police point out to each prisoner that cooperation will help reduce their sentence. If neither prisoner confesses, both will face one year in prison. If one testifies against his partner in crime, he will go free while the partner will get three years in prison on the main charge. But, if they both confess, that cooperation is not worth as much and both will be sentenced to two years in jail.

So, what should each prisoner do? No matter what the other prisoner does, confessing will improve their outcome, either from one year to none if the other does not confess, or from three years to two if the other does confess. So, the only rational thing to do is to confess. If both prisoners follow this logic, they will both get two years. And yet, if they had both kept quiet, it would have only been one year each, which would be better for both of them. The problem is that the “global optimum” is hard to obtain because there is too much of a risk for each prisoner that the other will defect.

The same is true for the high-frequency traders. While it might be cheaper for all of them to call a truce and freeze their technology at its current state, there would always be the risk that one firm breaks the truce and gains an edge. So, they all continue to compete in the speed race.

But the prisoner’s dilemma applies to more players than just the trading firms themselves.

If one of the major exchanges, such as the NASDAQ tried to stop the speed race, then it may well find itself losing business to any other exchange which continued to facilitate faster trading. An exchange without trading does not last long.

Governments too face the dilemma. There is already intense competition between exchanges operating in different countries and no government would want to lose the kudos and, more importantly, revenue that comes with playing host to a major financial centre. Would the UK government, for example, want to put London at a disadvantage to Europe or the US? Unlikely.

The German government is now delaying plans to curb high-frequency trading, in order to “clarify technical details”. I suspect that this will turn out to be a rather long delay.

The power and peril of FRED

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“FRED” is the St.Louis Federal Reserve Economic Database. It is an excellent repository of economic data, currently boasting 45,000 time-series from 42 data sources. The web-site offers a powerful interface for creating charts of FRED data. Unfortunately, it is a little too powerful, offering a rather dangerous feature: the secondary axis.

I have railed against secondary axes before. They tend to lure the viewer into seeing spurious correlations. Experimenting with FRED, Business Insider has fallen into exactly that trap. In an article entitled “PRESENTING: the ultimate oil currency“, Joe Weisenthal concludes that the euro is surprisingly highly correlated with the price of oil, particularly when oil prices are denominated in gold (OIL.XAU). His evidence is a chart created in FRED (courtesy of the site’s data transformation feature, which allows you to divide the Oil price in US dollars by the price of gold in US dollars).

Wiesenthal goes on to produce similar charts for the Australian dollar (AUD) and the Canadian dollar (CAD), concluding that they do not track the oil price nearly so well. With superimposed time-series like this, the eye is all too easily fooled into seeing correlations which do not exist. Simply separating the lines goes a long way to dispelling this illusion, as the charts below illustrate.

Looking at these charts, the strongest conclusion you would draw is that the euro and the oil price both went up in 2008, with the caveat that the euro started its run somewhat earlier, and the fell again towards the end of the year. At least you would probably agree with Wiesenthal that the Australian and Canadian dollars do not track the price of oil.

Rather than using two axes when comparing financial price histories, it is better to scale both series to a common value (say 100) at an initial point and plot the results against a single axis. Doing this for the euro and the price of oil shows that the rise in oil prices in mid 2008 was far sharper than that of the euro, as was the fall towards the end of the year.

If that chart is not enough to convince you that Wiesenthal’s euro/oil correlation is overblown, perhaps some statistics will help. The absolute price level of the time series is not important. What we need to measure is the correlation of returns (i.e. the percentage change in the prices)*. Daily returns might be a bit noisy, masking any correlations lurking in the data, so I have also calculated correlations for returns over a week (5 trading days) and a month (roughly 20 trading days).

	1 day Returns	5 day Returns	20 day Returns
AUD	35%	35%	47%
CAD	-35%	-34%	-46%
EUR	20%	15%	27%

Correlation of Returns to OIL.XAU

The correlation between the euro and the oil price is unimpressive, only reaching 27% for monthly returns. Perhaps surprisingly, it is the Australian dollar that shows the highest correlation to oil. Then again, that is probably only surprising after looking at Wiesenthal’s chart. After all, the Australian dollar is known as a “commodity currency”. But even for the Australian dollar, a 47% monthly return correlation for is not very high.

Once again, the lesson here is to beware of secondary axes. If I was running the FRED site, I would ban the feature immediately.

* The problems with computing correlations between serially correlated time series, such as price data, are well known. See for example Granger and Newbold, “Spurious Regressions in Econometrics” (1974).

Shadow Banking

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The Financial Services Authority (FSA) is the banking and financial services regulator in the UK. For now at least.

Back in 2010, the Chancellor of the Exchequer (the equivalent of the Treasury in Australian terms) announced plans to scrap the FSA in response to a failure during the financial crisis of the 10 year old “tri-partite system”. This tri-partite system split responsibility for national financial stability management between the Treasury, the Bank of England and the FSA. The government is now working on shifting responsibility back from the FSA to the Bank of England, a process which will establish three new regulatory bodies: the Financial Policy Committee (FPC), the Prudential Regulation Authority (PRA) and the Financial Conduct Authority (FCA). More three-letter initialisations and, dare I say it, a new tri-partite system?

Until this process is complete, the FSA continues about its business. The chairman of the FSA is Lord Adair Turner, Baron of Ecchinswell. Turner is also a member of the steering committee of the G20 Financial Stability Board (FSB). In March this year, he spoke at the London CASS business school on the topic of “shadow banking” and its role in the financial crisis.

Shadow banking, a term coined by Paul McCulley in the early days of the crisis, refers to a diverse range of entities such as “structured investment vehicles” (SIVs), hedge funds and money-market funds which have evolved to provide some very similar functions to banks, while not being subject to the same regulatory controls. A nightmare scenario for any bank is a “run”, when too many people try to withdraw their deposits at the same time. Shadow banks can also fall victim to runs. These runs may not be very obvious outside the financial markets, there are no queues of angry depositors on the streets, but they can be just as dangerous and runs on shadow banks were in fact a major factor underlying the global financial crisis. For this reason, regulators like Turner and the FSB are not only focused on strengthening controls on banks, but on better understanding shadow banks and, if possible, subjecting them to regulation to reduce the chances of future financial crises.

So what is it that shadow banks do? To answer that, I’ll first go back to the basics of banking. Although banks have evolved to provide many other products and services, the essence of banking is taking deposits and providing loans. The diagram below illustrates the flow of capital from an investor to a bank and from a bank to a borrower. Having given the bank some money, the investor now has a financial asset in the form of a deposit (and the deposit is a liability from the bank’s point of view). Likewise, the loan now represents a financial asset for the bank (and a liability from the borrower’s point of view). So the bank acts as intermediary between savers and borrowers. In doing so, however, banks act as more than a simple broker matching borrowers and lenders. Most bank lending also involves maturity transformation. More colloquially, this is known as lending long and borrowing short.

The typical depositor wants their money to be readily available in an at call transaction account. Some may be tempted by higher interest rates to put money in term deposits, usually no longer than 6 months to maturity. On the other hand, most borrowers do not want their loans due and payable too quickly. Home buyers borrow in the expectation that their earnings over coming years will allow them to pay interest and principal on their loans. Likewise, companies making capital expenditure, building factories, buying equipment or acquiring other businesses borrow in the expectation that the revenue generated by their expanded business capability will allow them to repay their loans. In both cases, the term of the loans must match the timeframes over which earnings are generated.

Some lenders will be prepared to make longer term investments, some borrowers may be able to repay more quickly, but overall there is a mismatch in maturity preferences of lenders and borrowers. Banks are in the business of bridging this gap in preferences. In the ordinary course of events, they can allow depositors to withdraw funds before loans are due to be repaid, making use of funds from other depositors, borrowing from other banks or, in need, borrowing from the central bank. But if too many borrowers withdraw at the same time and the bank is unable to meet those demands, then the bank can fail. This is known as liquidity risk, and has become an enormous focus of regulators, risk managers and rating agencies around the world in the wake of the global financial crisis.

While the financial crisis certainly highlighted the dangers of liquidity risk for commercial and investment banks such as Northern Rock and Lehman Brothers, it was outside the traditional banking sector that the greatest liquidity problems arose, particularly as a result of securitisation.

Securitisation is a form of structured finance that predates the financial crisis by many years. Essentially it involves setting up a trust (or similar legal entity) which provides loans that become the assets of the trust (often referred to as a “pool” of loans). The funds to provide these loans are obtained by selling a special kind of bond to investors, known as asset-backed securities (ABS). Principal and interest flowing from the loan pool is collected by the trust and periodically passed through to investors.

The most common form of securities bundles up pools of home loans, in which case they are referred to as residential mortgage-backed securities (RMBS).

Unlike bank-lending, there is essentially no maturity transformation involved in financing by means of ABS. Investors cannot withdraw their money early from the trust, they have to wait until it is repaid by borrowers. The only other option for an investor wanting to “liquidate” their investment (i.e. turn it back into cash) is to find another investor to sell their securities to.

The problem with ABS is the overall mismatch of maturity preferences between borrowers and lenders. Without getting into the business of maturity transformation, there was always going to be a limit on how large the market for ABS could become. Faced with a problem like this, it was only a matter of time before innovative financiers came up with a solution. One such solution was asset-backed commercial paper (ABCP). This involves adding another step in the chain, often referred to as a “conduit”. The conduit was simply another legal entity which would buy ABS, funding the purchase by issuing short-dated securities known as asset-backed commercial paper.

Just like a bank, the conduit is exposed to liquidity risk. Before the crisis, this risk was considered fairly low. After all, the assets of the conduit were readily trade-able securities. Most of the time the conduit could repay investors simply by issuing new ABCP to other investors but, in the unlikely event that no such investors could be found, it could simply sell the ABS. In some cases, investors were provided with additional assurance of repayment in the form of “liquidity backstops” provided by banks, essentially a guarantee that the bank would step in to repay investors in need (although these commitments were not always very clearly disclosed to bank shareholders). This whole arrangement was considered highly satisfactory and conduits typically received the highest possible rating from credit rating agencies.

Unfortunately, liquidity risk is a real risk as the world eventually discovered. Once the US mortgage market started to get into trouble in 2007, investors around the world began, quite reasonably, to be rather reluctant to invest in RMBS and other ABS. Prices on these securities began to fall. Managers of large-scale cash investment funds, until then enthusiastic buyers of ABCP, decided that more traditional cash investments were more attractive. The conduits were forced to sell ABS at precisely the time when prices were falling. Their selling pushed prices down further in a vicious cycle, a perfect illustration of the close relationship between funding liquidity risk (the risk of not being able to repay obligations) and market liquidity risk (the risk of being unable to sell financial assets at anything other than a painfully low price). As a result, some conduits were rescued by the banks backing them (“taking them back on balance sheet”), while others collapsed.

The problems of ABCP were just one example of non-bank liquidity failures during the financial crisis. Others include the venerable US money market fund, the Reserve Fund “breaking the buck” or Australian non-bank lender RAMS finding itself unable to continue funding itself by means of “extendible commercial paper” (ECP).

ABCP conduits, money-market funds, non-bank mortgage lenders along with many other non-bank financiers that make up the shadow banking sector had well and truly entered the business of maturity transformation and are all exposed to significant liquidity risk as a result. There are many linkages between banks and these shadow banks, whether through commitments such as liquidity backstops, direct lending or even partial or complete ownership. Regulators are concerned that too much risk in the shadow banking sector means too much risk for banks and too much risk for the financial system as a whole.

One strategy for regulators is to enforce a cordon sanitaire around banks, protecting them from shadow banks. But many, including Lord Turner, worry that is not enough to protect our global financial system with its complex interconnections from damage when shadow banks fail. Ideally they would like to regulate shadow banks as well, preventing them from running too much liquidity risk. But this is not an easy task. As the name suggests, it is not easy to see what is going on in the world of shadow banks, even for well-informed financial regulators.

Problem Pies

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Last month the IMF published their latest Global Financial Stability Report. A colleague, who knows I rarely approve of pie charts*, drew my attention to the charts on page 27 of Chapter 3 of the report, which I have reproduced here (click on the image to enlarge).

Here the authors of the report have decided to attempt some graphical improvisation, taking the pie chart and extending it. Over time some inspired new chart designs have been developed, but these have been rare. More often the result is inferior to using an established technique. While I do not wish to discourage innovation, the results should always be tested before being foisted on an unsuspecting audience.

The aim of this pair of charts is to illustrate the dwindling supply of “safe assets” in the form of highly rated sovereign debt as a result of the global financial crisis. For example, at the end of 2007, 68% of advanced economies boasted a AAA Standard & Poor’s credit rating (left hand chart, outer red arc) but by January 2012 this proportion had fallen to 52% (left hand chart, inner red sector).

The heart of each chart is a conventional pie chart showing the current distribution of country ratings. Taken in isolation, either one of these would be a reasonable chart. But moving beyond a single pie chart, comparing the Advanced Economies chart to the Emerging Markets chart is not so easy. Edward Tufte’s adage from The Visual Display of Quantitative Information comes to mind: “the only worse design than a pie chart is several of them”. The crime against charting here is made particularly egregious with the choice of a colour scheme for ratings that is not consistent across the two charts!

If that wasn’t bad enough, the design comes right off the rails with the outer charts. These are a form of annular pie chart, but the alignment of each segment is shifted in an attempt to make the pre-crisis figure more readily comparable to the post-crisis figure for each rating. The result is highly confusing: it takes a while to work out exactly what is going on. Messing with the alignment of the outer chart also makes it harder to compare one rating to another. Even the decision to position the 2012 data in the middle and the 2007 data on the outside is a mistake. My eye expects a flow from the centre of the circle outwards rather than from outside in. An informal, if statistically insignificant, survey suggests that I am not the only one with this expectation.

The aim of any data visualisation is to provide easy access to the information. Understanding the IMF report’s chart is just too much work. A simple table of figures would have been easier to understand. But there are also more conventional charts that would do a better job. The chart below is an example of the “small multiples” technique. This involves a grid of similar charts which are readily compared as certain parameters are varied. In this case, scanning the charts horizontally reveals changes through time and vertically the differences between advanced economies and emerging markets.

Sovereign ratings from before the crisis (2007) to now (2012)

Some space could have been saved by restricting the vertical axis to a 0% to 70% range, but with the full 0% to 100% range the proportions for each rating are more readily grasped.

The small multiples chart is a vast improvement on the IMF original, and is a good illustration of the fact that choosing the right chart makes it far easier to visualise the patterns in your data.

* One of the few pie charts I do approve of is this one (I have seen this one in many places, but I am not sure of the original source).

Bitcoin revisited

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Just over a year ago, I wrote about the digital “crypto-currency” Bitcoin. It has been an eventful year for Bitcoin.

Designed to provide a secure yet anonymous, decentralised means for making payments online, the first Bitcoins were virtually minted in 2009. By early 2011, Bitcoin had begun to attract attention. Various sites, including the not-for-profit champion of rights online, the Electronic Frontier Foundation (EFF), began accepting Bitcoins as payment. But when Gawker reported that Bitcoins could be used to buy drugs on “underground” website Silk Road, interest in the currency exploded and within a few days, the price of Bitcoins soared to almost $30.

This kind of attention was unwelcome for some, and shortly afterwards EFF announced that they would no longer be accepting Bitcoins, fearing that this would be construed as an endorsement of the now controversial currency. Around the same time, the first major theft of Bitcoins was reported and the Bitcoin exchange rate fell sharply.

Bitcoin Exchange Rate

More recently, another high-profile theft has caused ructions in the Bitcoin economy, prompting e-payments provider and PayPal competitor, Paxum, to abandon the Bitcoin experiment, which in turn forced one of the larger Bitcoin “exchanges” to shut down. The anonymity of Bitcoin is a design feature, but it also makes it almost impossible to trace thieves once they have their virtual hands on Bitcoins.

How much damage this does to the fledgling currency remains to be seen, but it certainly makes for a volatile currency. The free-floating Australian dollar is a reasonably volatile real-world currency but, as is evident in the chart below, Bitcoin volatility is an order of magnitude higher. That in itself is reason enough for any online business to think twice about accepting Bitcoins.

Rolling 30 day volatility (annualised)

Whatever its future, Bitcoin is a fascinating experiment and, even if it does not survive, digital currencies of one form or another are surely here to stay.

Data sources: Bitcoin charts, Bloomberg.

Bristol Pound

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Recently, a colleague drew my attention to the “Bristol Pound“, an example of a “local currency“. Ah yes, I said, that’s been around for a few years now. Embarrassingly, I later realised I was thinking about the “Brixton Pound“. Having attended many concerts at the legendary Brixton Academy (Nick Cave, Ministry and the Sugarcubes among them), I really should have known the difference between Bristol and Brixton!

There are now a number of local currencies in Britain. The first to appear in recent years was the “Totnes Pound“, launched in March 2007. According to their website, the benefits of the Totnes Pound are:

To build resilience in the local economy by keeping money circulating in the community and building new relationships
To get people thinking and talking about how they spend their money
To encourage more local trade and thus reduce food and trade miles
To encourage tourists to use local businesses

The aims of the Brixton Pound, the Bristol Pound and the other local currencies are essentially the same. As far as I can tell, the take up of these currencies to date has been modest, but the Bristol Pound represents an interesting new development. Not only does it have a far slicker website, but it also offers payment by mobile phone. Perhaps most significantly, according to the FAQ, “Business members that pay business rates to Bristol City Council will be able to pay in Bristol Pounds.”

A key tenet of “Modern Monetary Theory” is that the value of fiat money is not underpinned by gold or any other commodity; rather its value derives from the government levying tax in that currency. Since almost everyone has to pay tax at some point, this creates a base level of demand for the currency. So, perhaps the fact that the Bristol City Council is supporting the Bristol Pound will enhance its take-up prospects. It would be even more interesting if the council decided that they would only accept Bristol Pounds as payment for rates.

Ring-fencing rogue traders

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Kweku Adoboli managed to cost UBS over $2 billion with his rogue trading, and has now cost chief executive Oswald Grübel his job. While this time the buck stopped at the top, it is more than can be said for many previous rogue trading cases. Grübel was called out of retirement to take the helm of UBS as it faced the global financial crisis, so perhaps a return to retirement was an easier choice than it would have been for the chief executives of Société Générale, NAB*, Allied Irish and other past victims of rogue traders.

But what has surprised me about this latest rogue trading incident is reactions like this one from the Economist:

For UBS and its shareholders, the immediate questions should be why it was still vulnerable to this sort of alleged manipulation more than three years after Mr Kerviel’s [the Société Générale rogue trader] loss.

Of course banks are aware of the risk of rogue trading, but it does not mean that protecting themselves against this risk is a simple matter. Trading businesses are complex, with many interconnected computer systems, some old, some new, most dealing with transactions in real time. It is a case of asymmetric warfare: the bank has to defend itself against every possible attack, but the rogue trader only has to find a single point of weakness. The UBS loss may be another reminder for banks of just how much an insider can cost them, but I am confident that there will be another spectacular rogue trading case within the next five years.

Little wonder then that Sir John Vickers, in his report on UK banking, has recommended that banks should “ring-fence” their investment banking operations (including financial markets trading businesses) from their retail and commercial banking arms. The idea is that, while governments will always want to protect the financial system that is so central to their economy, tax-payers should not end up on the hook for losses arising from risky investment banking activity.

Banking regulators around the world have been intently pursuing ideas like this over the last couple of years and the Adoboli case will only add to their determination to impose some form of “recovery and resolution” framework on banks. Before this work is complete, I would not be too surprised if UBS have spun off their investment banking arm. It is becoming all a bit much for Swiss shareholders to cope with.

* UPDATE: My memory served me poorly: the CEO of NAB, Frank Cicutto, did in fact resign after their FX trading fraud.

Gibbons and welfare

Why deficits are bad

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There have been many posts here on the blog arguing that government debt and deficits should not be feared, at least not in countries with their own free-floating currency and without foreign currency public debt*. In doing so, I have never discussed the reasons people may have for holding a contrary view. But I have now come across a rather disturbing theory on the news site Alter.net.

It may be that there are some who would like to see an end to government deficits because they adhere to the Chicago school of economics and scoff that Keynes was thoroughly discredited by the stagflation of the 1970s. There may be others who challenge supporters of government spending with a simple question: if too much debt was the cause of the financial crisis, how could more debt be the answer? (Of course, regular readers of the blog will know the answer to this one: the debt build-up before the crisis was private sector debt and for the private sector to reduce debt by saving again, the government must run a deficit**). Still others may think that deficits cause recessions (rather than recessions causing deficits).

But the theory offered by Alter.net is simpler still. Perhaps people think national debt is bad because it actually means a bad economy. Literally. They just do not understand the meaning of the words.

The evidence offered goes back to a US presidential debate from 1992. In the debate, an audience member asks the candidates the following question:

How has the national debt personally affected each of your lives. And if it hasn’t, how can you honestly find a cure for the economic problems of the common people if you have no experience in what’s ailing them?

If you watch the resulting exchange here, it quickly becomes clear that, in the questioner’s mind, “national debt” is in fact synonymous with “recession”. National debt doesn’t cause unemployment, it is unemployment!

Of course that clip is almost 20 years old and it is America, not Australia. But it still worries me. Could it be that part of the reason that it is so hard to have a rational debate about debt and deficits is that some (or even many) of the voting public do not understand what the debate is about? I hope not!

* So the eurozone is a different matter altogether!

** Either that or run a current account surplus…which is still something we have not achieved in Australia.

High-frequency trading

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In a recent episode, the ever-brilliant Planet Money podcast looked at the arcane world of high-frequency trading. The usual clarity of exposition was further enhanced by something of a Mule theme. It seems that Planet Money host Chana Joffe-Walt is, like me, a Tom Waits enthusiast and she found a way to fuse “Whats He Building in There?” from the Mule Variations album with the otherwise non-musical subject of the podcast. An inspired choice.

So, what is high-frequency trading? Here is how Planet Money describes it.

In high-frequency trading, people program computers to buy and sell stocks in quick succession under certain, pre-defined circumstances. The idea is to profit from fleeting changes in the price of a stock.

This type of trading is made possible by the increased use of electronic trading platforms for financial markets around the world and is a special case of so-called “algorithmic trading” (or “algos”). It has been estimated that as much as 75% of the trades on the New York stock exchange were generated by algos and perhaps 50% on some European markets.

High-frequency trading has been generating some controversy in recent years:

High-frequency traders often confound other investors by issuing and then canceling orders almost simultaneously. Loopholes in market rules give high-speed investors an early glance at how others are trading. And their computers can essentially bully slower investors into giving up profits — and then disappear before anyone even knows they were there.

Critics of high-frequency trading argue that it is a form of front-running, a practice which is illegal in most jurisdictions. The counter-argument in defence of the algos is that it increases the efficiency of the market. As Steve Rubinow of NYSE Euronext explains to Planet Money:

Every innovation of this type makes the market more efficient. … The faster we trade, and the more people you have trading, any aberrations that exist in the market are taken out of the market really really quickly, which makes for a fairer market for all participants … Those prices are about as fair as they could be.

Efficient markets are a good thing and I have used a similar argument here on the blog to defend short-selling. Nevertheless, there has always been something about high-frequency trading that makes me uneasy. In an interview with Edge, Emanuel Derman seems to put the finger on the source of this unease:

Also, people who benefit from it tend to over-accentuate the need for efficiency. Everybody who makes money out of something to do with trading tends to say, oh, we’re got to do this because it makes the market more efficient. But a lot of the people who provide this so-called liquidity and efficiency are not there when you really need it. It’s only liquidity when the world is running smoothly. When the world is running roughly, they can withdraw their liquidity. There is no terrible need to be allowed to trade large amounts in fractions of a second. It’s kind of a self-serving argument. Maybe a tax on trading to insert some friction isn’t a bad idea, just as long term capital gains are taxed lower than short term gains.

Derman started working as a “quant” in financial market around 25 years ago and had a long stint at Goldman Sachs. His response is not likely to be one of knee-jerk suspicion, but rather the considered voice of experience.

Joffe-Wolt’s reinterpretation of Waits conjured up an atmosphere of mystery and fear when exploring NYSE Euronext’s new data centre. Perhaps a bit of fear of high-frequency trading is healthy.

Image Source: Discogs

Stubborn Mule

Obstinately objective